Data-Driven Modeling of Control Valve Stiction Using Revised Binary-Tree Structure

An accurate stiction model enables the detection, quantification, and compensation of this nonlinear phenomenon in a control valve. Compared with stiction models obtained from physical laws, data-driven models are more popular because of their simplicity in terms of the number of parameters required...

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Bibliographic Details
Published inIndustrial & engineering chemistry research Vol. 54; no. 1; pp. 330 - 337
Main Authors Li, XiaoCong, Chen, Si-Lu, Teo, Chek Sing, Tan, Kok Kiong, Lee, Tong Heng
Format Journal Article
LanguageEnglish
Published American Chemical Society 14.01.2015
Subjects
Accuracy
Control valves
Industrial engineering
Mathematical models
Nonlinearity
Stiction
Trees
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Summary:An accurate stiction model enables the detection, quantification, and compensation of this nonlinear phenomenon in a control valve. Compared with stiction models obtained from physical laws, data-driven models are more popular because of their simplicity in terms of the number of parameters required. In this work, the previously proposed two-layer binary tree data-driven stiction model is revised to overcome its limitations in handling instantaneous input commands on reverse motion. Then, the accuracy of the revised model is validated using the full set of ISA control valve standard tests. From these results, its advantages over other major existing data-driven models are indicated in terms of simplicity and accuracy.
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ISSN:0888-5885
1520-5045
DOI:10.1021/ie5031369